We are looking for a Data Engineer to join our Data &amp; Analytics team in Houston, Texas, and help strengthen the reporting foundation that supports decisions across the business. In this role, you will shape data into reliable, business-ready models, develop scalable reporting structures, and work closely with teams such as Finance and Operations to turn complex rules into clear insights. This position blends technical data engineering with analytics-focused development, offering the opportunity to improve reporting quality, maintain dependable data flows, and contribute to ongoing enhancements in our analytics environment.<br><br>Responsibilities:<br>• Develop and maintain structured data models, including staging layers, reporting tables, and dimensional designs within the Azure-based data warehouse environment.<br>• Create and support Power BI semantic models, calculated measures, security configurations, dashboards, and reports used for operational and enterprise reporting.<br>• Monitor scheduled data workflows and dataset refresh activity, investigate processing issues, and resolve failures to keep reporting available and accurate.<br>• Adjust and enhance existing ETL and orchestration processes as business needs evolve, using tools such as Azure Data Factory and related Microsoft data platforms.<br>• Collaborate with stakeholders across functions to translate reporting needs, financial logic, and operational rules into dependable analytical solutions.<br>• Produce clear technical and business documentation covering model design, metric definitions, transformation logic, and data ownership.<br>• Apply and help refine development standards for naming, modeling approach, query design, and reporting structure to improve consistency and quality.<br>• Identify opportunities to streamline current data practices, improve performance, and introduce effective tools or methods that strengthen analytics capabilities.

• Strong experience building Power BI semantic models from the ground up, including advanced DAX and an understanding of filter behavior and calculation context.<br>• Solid knowledge of dimensional modeling concepts such as star schemas and slowly changing dimensions.<br>• Proven ability to work directly with business stakeholders and convert loosely defined requirements into practical data models and reporting outputs.<br>• High attention to data accuracy, with the ability to identify issues related to joins, logic gaps, and boundary conditions that can affect reporting results.<br>• Hands-on experience with SQL and T-SQL for querying, transforming, and validating data.<br>• Familiarity with ETL processes and data engineering tools or platforms such as Python, Apache Spark, Hadoop, Kafka, or similar technologies.<br>• Exposure to orchestration and modern Microsoft data platforms, including Azure Data Factory and Microsoft Fabric, is preferred.<br>• Basic experience with source control practices such as Git is an advantage.

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